Table 2.

General considerations for protein-protein interactome studies

Consideration	Problem	Solution
Localization	•proteins of different organelles differ in their solubility in standard lysis buffers used for PPI studies (Orre et al., 2019; Peach et al., 2015)	•reagents such as digitonin and n-dodecyl-b-D-maltoside (DDM) can be used •subcellular fractionation to reduce any common contaminants •use the Human Protein Atlas and SubCellBarcode portal to confirm the localization of proteins
	•variation in the pH, redox environment, and nucleophile concentrations can affect the activity of BirA enzymes (Branon et al., 2018)	•choosing the right BirA enzyme; TurboID outperforms BioID and miniTurbo in the mitochondrial matrix, nucleus, and ER lumen (Branon et al., 2018)
Molecular weight	•large proteins (>200 kDa) are usually poorly solubilized and affinity purified	•divide the large protein into segments and express independently
Epitope tags or fusions	•may prevent some interactions •may lead to protein misfolding and malfunction •some tags lead to protein dimerization (Sharifi Tabar et al., 2022b; Torrado et al., 2017)	•use small epitope tags such as FLAG and HA combined with flexible linkers •examine both N- and C-terminal tags and compare the efficiency
Cell culture medium	•the presence of biotin in cell culture medium can lead to autonomous protein biotinylation and interfere with BioID results	•choose a cell line that can grow in media containing minimal or no biotin
Controls	•inappropriate control(s) can lead to identification of both false negative and false positive interactions	•for IP-MS, a gene knockout cell line can be used rather than using isotype control serum •for PL-MS, use an empty vector carrying the BirA protein •for PD-MS, use an empty vector carrying the same epitope tag
Quality of the beads	•variations in streptavidin beads or affinity resins (agarose or magnetic) (St-Germain et al., 2020)	•store beads in appropriate conditions •use the same batch of beads for the entire experiment
Quantitation method	•label-free approaches suffer from low accuracy and false positive hits •label-based proteomic approaches (e.g., SILAC) are expensive and time consuming (Taverna and Gaspari, 2021)	•increase the number of control samples to reduce the chance of false positives